Sensor Serat Optik Dengan Cladding Polianilin Nanostruktur Untuk Mendeteksi Uap Hcl

Telah dikembangkan sistem sensor serat optik untuk mendeteksi uap HCl, dengan polianilin nanostruktur (nanofiber) sebagai cladding sensitif pengganti cladding asli serat optik. Mekanisme transduksinya didasarkan pada Perubahan sifat optik cladding polianilin nanostruktur ketikaberinteraksi dengan uap HCl, sehingga absorpsi gelombang evanescent berubah. Polianilin nanostruktur berbentuk nanoserat disintesis dengan metode polimerisasi interfasial. Sifat optik polianilin memperlihatkan Perubahan spektrum absorpsi spesifik terhadap perlakuan uap HCl. Pasta polianilin dilapiskan pada bagian inti serat optik plastik sepanjang 2 cm yang telah dilepas cladding aslinya, sebagai elemen pengindera. Uji respon sensor serat optik terhadap uap HCl dilakukan dengan mengukur intensitas cahaya yang melewati elemen sensor (probe), data intensitas diambil terhadapwaktu secara real-time berbasis komputer. Kurva siklus respon sensor diperoleh dengan cara memasukkan dan mengeluarkan bagian sensing ke dalam wadah uap HCl secara berulang. Hasil uji respon berupa kurva siklus nilai intensitas terhadap waktu menampilkan karakteristik bagian respon dan pemulihan (recovery). Dari kurva siklus respon tersebut diperoleh waktu respon dan waktu pemulihan yang sangat singkat yaitu sekitar 18 detik. Sensor serat optik ini memiliki kemampuanpembalikan (reversibility) dan pengulangan (repeatebility) yang baik pula.Fiber-optic sensor for detection of HCl vapor has been developed, where the origin cladding of fiberoptic was replaced with nanosructure polyaniline as sensitive cladding. Transduction mechanism was based on changes of optical properties of nanostructure polyaniline cladding when interacts with HCl vapor, so the absorption of evanescent wave was changes. Nanostructure polyaniline in nanofiber form was synthesized by interfacial polymerization. Optical properties of polyaniline show a change of specific optical absorption when exposed with HCl vapor. Polyaniline paste was coated onto coresurface of uncladded fiber optic as long 2 cm, as a sensing element. Sensor response to HCl vapor was tested by measuring intensity of light transmitted trough sensing element, intensity versus time was real-time acquired using computer. Cyclic response curve of the sensor was obtained by inserting and withdrawing the sensing element into and out from HCl vapor container repeatedly. The test result of response be a cyclic curve of intensity versus time shows a set of response and recovery region. Regarding the curve of the response cycle was determined a response and recovery time very short time, it about of 18 second. The sensor has a good reversibility and repeatability

Méthodes de rééchantillonnage pour l'estimation de variance

Nous passons en revue des techniques de rééchantillonnage utilisées pour l'estimation de variance en sondage. Les techniques de rééchantillonnage considérées sont basées sur la linéarisation, le jackknife, les répétitions équilibrées répétées, et le bootstrap. Quelques unes des procédures d'estimation de variance utilisent des mécanismes de calibration et d'imputation afin d'améliorer l'estimation. Notre objectif est d'obtenir des conclusions pratiques basées sur des considérations théoriques et des comparaisons empiriques

Resamping variance estimation in surveys with missing data

We discuss variance estimation by resampling in surveys in which data are missing. We derive a formula for jackknife linearization in the case of calibrated estimation with deterministic regression imputation, and compare the resulting variance estimates with balanced repeated replication with and without grouping, the bootstrap, the block jackknife, and multiple imputation, for simulated data based on the Swiss Household Budget Survey. Jackknife linearisation, the bootstrap, and multiple imputation perform best in terms of relative bias and mean square error

Pengembangan Probe Sensor Kelembaban Serat Optik Dengan Cladding Gelatin

Development of Fiber-Optic Humidity Sensor Probe with Gelatin Cladding. Humidity sensor based on optical fiberwith gelatin cladding has been developed. In this humidity sensor probe, the origin cladding of optical fiber is replacedby gelatin coating as humidity sensitive cladding. Testing of the optical fiber sensor probe was conducted by measuringof light intensity transmitted on the optical fiber probe for each variation of different humidity treatments. Response ofthe optical fiber sensor probe measured from 42%RH to 99%RH, the results show an optical transmission curve variedwith relative humidity (RH). Optical transmission in the optical fiber probe increase with RH value at a specificwavelength range, that is from green to red spectrum bands (500 nm - 700 nm), where a significant variation from 600nm to 650 nm in yellow to red spectrum bands. Wavelength where is a maximum intensity of optical transmissionoccurs at 610 nm. Therefore, the optical fiber humidity sensor probe could response humidity form 42%RH to 99%RHwith the best response in humidity range of 60%RH to 72%RH that is have a good linearity and sensitivity

Adaptive noise cancelling and time–frequency techniques for rail surface defect detection

Adaptive noise cancelling (ANC) is a technique which is very effective to remove additive noises from the contaminated signals. It has been widely used in the fields of telecommunication, radar and sonar signal processing. However it was seldom used for the surveillance and diagnosis of mechanical systems before late of 1990s. As a promising technique it has gradually been exploited for the purpose of condition monitoring and fault diagnosis. Time-frequency analysis is another useful tool for condition monitoring and fault diagnosis purpose as time-frequency analysis can keep both time and frequency information simultaneously. This paper presents an ANC and time-frequency application for railway wheel flat and rail surface defect detection. The experimental results from a scaled roller test rig show that this approach can significantly reduce unwanted interferences and extract the weak signals from strong background noises. The combination of ANC and time-frequency analysis may provide us one of useful tools for condition monitoring and fault diagnosis of railway vehicles

Divergent in situ expression of IL-31 and IL-31RA between bullous pemphigoid and pemphigus vulgaris

Bullous pemphigoid (BP) and pemphigus vulgaris (PV) are two major autoimmune blistering skin diseases. Unlike PV, BP is accompanied by intense pruritus, suggesting possible involvement of the pruritogenic cytokine IL-31. However, the underlying mechanisms of the clinical difference between BP and PV in terms of pruritus are not fully understood. To compare the expression levels of IL-31 and its receptor IL-31RA in the lesional skin, including peripheral nerves in BP and PV patients, immunohistochemical staining for IL-31 and IL-31RA was performed in skin samples of BP and PV patients and healthy controls (HC). The IL-31RA-expressing area in epidermis and peripheral nerves was analysed using ImageJ and the percentage of positive cells for IL-31/IL-31RA in dermal infiltrating cells was manually quantified. Quantitative analyses revealed that IL-31/IL-31RA expressions in the epidermis and dermal infiltrate were significantly increased in BP compared to PV and HC. The difference between BP and PV became more obvious when advanced bullous lesions were compared. Peripheral nerves in BP lesions presented significantly higher IL-31RA expression compared to PV lesions. In conclusion, we found significantly augmented expressions of IL-31/IL-31RA in BP lesions, including peripheral nerves, in comparison to PV. These results suggest a possible contribution of IL-31/IL-31RA signalling to the difference between BP and PV in the facilitation of pruritus and local skin inflammation, raising the possibility of therapeutic targeting of the IL-31/IL-31RA pathway in BP patients

BARD1 serum autoantibodies for the detection of lung cancer

Purpose Currently the screening for lung cancer for risk groups is based on Computed Tomography (CT) or low dose CT (LDCT); however, the lung cancer death rate has not decreased significantly with people undergoing LDCT. We aimed to develop a simple reliable blood test for early detection of all types of lung cancer based on the immunogenicity of aberrant forms of BARD1 that are specifically upregulated in lung cancer. Methods ELISA assays were performed with a panel of BARD1 epitopes to detect serum levels of antibodies against BARD1 epitopes. We tested 194 blood samples from healthy donors and lung cancer patients with a panel of 40 BARD1 antigens. Using fitted Lasso logistic regression we determined the optimal combination of BARD1 antigens to be used in ELISA for discriminating lung cancer from healthy controls. Random selection of samples for training sets or validations sets was applied to validate the accuracy of our test. Results Fitted Lasso logistic regression models predict high accuracy of the BARD1 autoimmune antibody test with an AUC = 0.96. Validation in independent samples provided and AUC = 0.86 and identical AUCs were obtained for combined stages 1-3 and late stage 4 lung cancers. The BARD1 antibody test is highly specific for lung cancer and not breast or ovarian cancer. Conclusion The BARD1 lung cancer test shows higher sensitivity and specificity than previously published blood tests for lung cancer detection and/or diagnosis or CT scans, and it could detect all types and all stages of lung cancer. This BARD1 lung cancer test could therefore be further developed as i) screening test for early detection of lung cancers in high-risk groups, and ii) diagnostic aid in complementing CT scan

Polymorphisms in the Mitochondrial Genome Are Associated With Bullous Pemphigoid in Germans

Bullous pemphigoid (BP) is the most prevalent autoimmune skin blistering disease and is characterized by the generation of autoantibodies against the hemidesmosomal proteins BP180 (type XVII collagen) and BP230. Most intriguingly, BP is distinct from other autoimmune diseases because it predominantly affects elderly individuals above the age of 75 years, raising the question why autoantibodies and the clinical lesions of BP emerges mostly in this later stage of life, even in individuals harboring known putative BP-associated germline gene variants. The mitochondrial genome (mtDNA) is a potential candidate to provide additional insights into the BP etiology; however, the mtDNA has not been extensively explored to date. Therefore, we sequenced the whole mtDNA of German BP patients (n = 180) and age- and sex-matched healthy controls (n = 188) using next generation sequencing (NGS) technology, followed by the replication study using Sanger sequencing of an additional independent BP (n = 89) and control cohort (n = 104). While the BP and control groups showed comparable mitochondrial haplogroup distributions, the haplogroup T exhibited a tendency of higher frequency in BP patients suffering from neurodegenerative diseases (ND) compared to BP patients without ND (50%; 3 in 6 BP with haplogroup T). A total of four single nucleotide polymorphisms (SNPs) in the mtDNA, namely, m.16263T>C, m.16051A>G, and m.16162A>G in the D-loop region of the mtDNA, and m.11914G>A in the mitochondrially encoded NADH:ubiquinone oxidoreductase core subunit 4 gene (MT-ND4), were found to be significantly associated with BP based on the meta-analysis of our NGS data and the Sanger sequencing data (p = 0.0017, p = 0.0129, p = 0.0076, and p = 0.0132, respectively, Peto's test). More specifically, the three SNPs in the D-loop region were negatively, and the SNP in the MT-ND4 gene was positively associated with BP. Our study is the first to interrogate the whole mtDNA in BP patients and controls and to implicate multiple novel mtDNA variants in disease susceptibility. Studies using larger cohorts and more diverse populations are warranted to explore the functional consequences of the mtDNA variants identified in this study on immune and skin cells to understand their contributions to BP pathology

Wavelet penalized likelihood estimation in generalized functional models

The paper deals with generalized functional regression. The aim is to estimate the influence of covariates on observations, drawn from an exponential distribution. The link considered has a semiparametric expression: if we are interested in a functional influence of some covariates, we authorize others to be modeled linearly. We thus consider a generalized partially linear regression model with unknown regression coefficients and an unknown nonparametric function. We present a maximum penalized likelihood procedure to estimate the components of the model introducing penalty based wavelet estimators. Asymptotic rates of the estimates of both the parametric and the nonparametric part of the model are given and quasi-minimax optimality is obtained under usual conditions in literature. We establish in particular that the LASSO penalty leads to an adaptive estimation with respect to the regularity of the estimated function. An algorithm based on backfitting and Fisher-scoring is also proposed for implementation. Simulations are used to illustrate the finite sample behaviour, including a comparison with kernel and splines based methods

Wavelet-based identification of DNA focal genomic aberrations from single nucleotide polymorphism arrays

<p>Abstract</p> <p>Background</p> <p>Copy number aberrations (CNAs) are an important molecular signature in cancer initiation, development, and progression. However, these aberrations span a wide range of chromosomes, making it hard to distinguish cancer related genes from other genes that are not closely related to cancer but are located in broadly aberrant regions. With the current availability of high-resolution data sets such as single nucleotide polymorphism (SNP) microarrays, it has become an important issue to develop a computational method to detect driving genes related to cancer development located in the focal regions of CNAs.</p> <p>Results</p> <p>In this study, we introduce a novel method referred to as the wavelet-based identification of focal genomic aberrations (WIFA). The use of the wavelet analysis, because it is a multi-resolution approach, makes it possible to effectively identify focal genomic aberrations in broadly aberrant regions. The proposed method integrates multiple cancer samples so that it enables the detection of the consistent aberrations across multiple samples. We then apply this method to glioblastoma multiforme and lung cancer data sets from the SNP microarray platform. Through this process, we confirm the ability to detect previously known cancer related genes from both cancer types with high accuracy. Also, the application of this approach to a lung cancer data set identifies focal amplification regions that contain known oncogenes, though these regions are not reported using a recent CNAs detecting algorithm GISTIC: SMAD7 (chr18q21.1) and FGF10 (chr5p12).</p> <p>Conclusions</p> <p>Our results suggest that WIFA can be used to reveal cancer related genes in various cancer data sets.</p